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SUMMARY:Disease modelling: how to control and prevent epidemic outbreaks
DTSTART;VALUE=DATE-TIME:20180712T013000Z
DTEND;VALUE=DATE-TIME:20180712T015000Z
DTSTAMP;VALUE=DATE-TIME:20210228T010727Z
UID:indico-contribution-323@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Elena Aruffo ()\nIn recent years vaccination studies
  have led to greater understanding and improvements on the development and
  distribution of vaccines\, especially with respect to certain childhood d
 iseases. However\, while current vaccination campaigns strive to achieve h
 erd immunity (a critical threshold of ‘immune’ individuals needed to p
 rotect an entire population from infection)\, eradication has not been ach
 ieved and populations continue to be affected by childhood diseases global
 ly. These outbreaks are usually attributed to the movement of one or more 
 asymptomatic cases from a country affected by the pathogen in question. Ne
 vertheless\, individuals coming from regions with infection-induced immuni
 zation can provide protection to the receiving region. Mathematical models
  are able to describe the dynamics of an infectious diseases in population
 s\, and they can provide important measurements for public health such as 
 the basic reproductive ratio\, the vaccination threshold needed to achieve
  herd immunity\, and project the number of cases that could be observed du
 ring an outbreak. In particular\, metapopulation models can be used to tra
 ck the movement of individuals through travel or immigration to better und
 erstand the movement and persistence of infectious diseases\, and border r
 estriction policies. We propose infectious disease models to study the dis
 tribution of immunity in a population and how this changes with immigratio
 n and travel\, by using a Susceptible-Exposed-Infectious-Recovered framewo
 rk. Our work is in collaboration with Public Health Ontario and has been u
 sed to better understand the effects of measles immunity in a population. 
 Our results show that the biggest loss in the susceptible population happe
 ns when the infected individual introduced in the population belongs to th
 e group of children between 5 and 9 years\, even when vaccination threshol
 ds recommended by the WHO are achieved.\n\nhttps://conferences.maths.unsw.
 edu.au/event/2/contributions/323/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/323/
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